The invention relates generally to fabricated parts, and more specifically to a performance predictor for fabricated parts, typically molded parts.
Thin-walled parts have been in increasingly higher demand in recent years. Part costs have driven the trend to thinner walls. Less material and shorter cycle times have made thin-wall applications popular with cost-conscious end users.
Examples of thin-wall molded parts include not only smaller parts like cellular phones, Personal Digital Assistants (PDAs), and laptop computer housings, but also larger parts like housings for computer monitors, and parts as large as automotive instrument panels.
Two of the most expensive tasks in the development of thin-wall molding applications are the pre-production molding trials and modifications to the tooling necessary to meet end use requirements. The uncertainties in the processing window and tooling design are the result of interactions among the material properties, the thin-wall part geometry, and the part performance.
Most process and tooling designers in the plastics injection molding community understand that it is quite difficult to design an injection mold for thin-wall parts without potential cut-and-trials, but at the same time they have failed to develop a clear definition for “thin-wall” itself. Some think that if the minimum wall thickness is less than a certain value then the part is considered to be thin-wall, while others think that the ratio between the filling distance for each gate and the minimum wall thickness should be the criterion. These definitions are not wrong, but they are only partially correct. Both criteria depend too much on the size of the part being molded, and neither considers the structural requirements of the application.
Once the basic engineering mechanics associated with this challenging problem have been considered, it is found that the viscous heating, or the viscosity times the square of the shear rate, is what makes the thin-wall applications unique in the injection molding process and tooling design area. This viscous heating couples the momentum (force) and energy (temperature) balances. An increase of 10° C. to 40° C. in the resin temperature is not uncommon for thin-wall applications.
Through the definition of the shear rate, it is apparent that thin walls or fast flow rates would produce higher shear rates. However, there is another way of developing an equivalent thin-wall condition—as the instantaneous solidified layer buildup is generated during the filling stage, a thin-wall condition could develop for the case of conventional wall thickness parts with long filling distances and fairly low flow rates, which could generate these high shears.
For the case of conventional molding, there is only a weak coupling between the momentum and energy equations through the temperature-dependent viscosity. Therefore, one can solve the pressure and temperature in a sequential manner, providing the temperature field for the viscosity calculation. However, it is much more complicated in the thin-wall case where both equations are strongly coupled through the viscous heating term, which feeds the calculated shear rate in the momentum equation back to the energy equation. This full coupling phenomenon is the core technical challenge in the development of a numerical thin-wall performance predictor. Without robust numerical algorithms, it would be impossible to predict pressure, shear rate and temperature correctly in such a complex physical system and an accurate prediction of these filling parameters is a prerequisite for predicting the failure mechanism of thin-wall molded parts.
The technology does not currently exist in the commercial mold-filling analysis codes to accurately predict the behavior of thin-walled parts in terms of the pressure, shear rate and temperature, which is a prerequisite for predicting the failure behavior. The commercial codes are good at predicting the behavior of parts that have conventional wall thicknesses, but they cannot predict the behavior of thin-walled parts because, in part, they lack improved algorithms, solution coupling and stability conditions.
In recent years, much research work has been done in linking processing conditions to warpage or shrinkage behavior through numerical simulation. This work is mostly focused on predicting failure induced by shear and thermal degradation during processing by combining numerical simulation and empirical databases.
Traditionally, impact performance depends on three factors, namely, the stress state, strain rate, and temperature. For parts produced through conventional molding, a mechanical impact theory based on these three factors is sufficient to provide reliable part performance results. However, in order to ensure complete filling, the molding of thin-wall parts requires much higher injection speeds and injection pressures, which typically lie outside the range of processing parameters used in conventional molding. These thin-wall molding conditions can generate very high shear rates in the part. Due to the viscous heating effects, the temperature can rise dramatically in the high shear regions (e.g., areas near the gate). Typical temperature increases can be as large as 40° C. Because of the extremely high shear and temperature conditions that a material can experience during thin-wall molding, the resulting parts are subject to both shear degradation (i.e., high shear) and thermal degradation (i.e., viscous heating). Shear and thermal degradation could potentially turn out to be significant factors that affect the impact performance of thin-wall parts. Therefore, a robust and reliable predictive methodology for thin-wall applications should incorporate the effects of shear and thermal degradation in addition to the traditional factors such as stress state, strain rate, and temperature.
Accordingly, there is a need for an improved performance predictor for fabricated parts.